Bottom Line:
To better understand the universe of antibody responses that develop after B. melitensis infection, a protein microarray was fabricated containing 1,406 predicted B. melitensis proteins.Based on these results, a nitrocellulose line blot containing the human serodiagnostic antigens was fabricated and applied in a simple assay that validated the accuracy of the protein microarray results in the diagnosis of humans.These data demonstrate that an experimentally infected natural reservoir host produces a fundamentally different immune response than a naturally infected accidental human host.

ABSTRACTBrucellosis is a widespread zoonotic disease that is also a potential agent of bioterrorism. Current serological assays to diagnose human brucellosis in clinical settings are based on detection of agglutinating anti-LPS antibodies. To better understand the universe of antibody responses that develop after B. melitensis infection, a protein microarray was fabricated containing 1,406 predicted B. melitensis proteins. The array was probed with sera from experimentally infected goats and naturally infected humans from an endemic region in Peru. The assay identified 18 antigens differentially recognized by infected and non-infected goats, and 13 serodiagnostic antigens that differentiate human patients proven to have acute brucellosis from syndromically similar patients. There were 31 cross-reactive antigens in healthy goats and 20 cross-reactive antigens in healthy humans. Only two of the serodiagnostic antigens and eight of the cross-reactive antigens overlap between humans and goats. Based on these results, a nitrocellulose line blot containing the human serodiagnostic antigens was fabricated and applied in a simple assay that validated the accuracy of the protein microarray results in the diagnosis of humans. These data demonstrate that an experimentally infected natural reservoir host produces a fundamentally different immune response than a naturally infected accidental human host.

pntd-0000673-g004: Multiple Antigen LOOCV ROC curves.The LOOCV ROC graphs show classifiers with increasing number of human serodiagnostic antigens. Overall, the sensitivity and specificity for array test is over 95%.

Mentions:
To establish a collection of antigens able to accurately distinguish brucellosis cases from controls, leave one out cross-validation (LOOCV) receiver operating characteristic (ROC) curves were generated for individual serodiagnostic antigens to assess the ability to separate the control and disease cases (Fig. 4). The serodiagnostic antigens were ordered by decreasing single antigen area under the curve (AUC). The top ten ORFs all have an AUC greater than 0.734 (Table 1), with BP26 (BMEI0536; AUC 0.983; Benjamini and Hochberg adjusted Cyber-T p-value<10e-16) giving the best single antigen discrimination with sensitivity and specificity 91% and 96% (Fig. 4), respectively. We used kernel methods and support vector machines [47], [63] to build linear and nonlinear classifiers. As input to the classifier, we used the highest-ranking 1, 2, 5, 10, 13 ORFs on the basis of single antigen AUC. The results show that increasing the antigen number from 2 to 5 produced an improvement in sensitivity and specificity (Fig. 4). This classifier yielded a high sensitivity and specificity rate of 95% and 96%, respectively.

pntd-0000673-g004: Multiple Antigen LOOCV ROC curves.The LOOCV ROC graphs show classifiers with increasing number of human serodiagnostic antigens. Overall, the sensitivity and specificity for array test is over 95%.

Mentions:
To establish a collection of antigens able to accurately distinguish brucellosis cases from controls, leave one out cross-validation (LOOCV) receiver operating characteristic (ROC) curves were generated for individual serodiagnostic antigens to assess the ability to separate the control and disease cases (Fig. 4). The serodiagnostic antigens were ordered by decreasing single antigen area under the curve (AUC). The top ten ORFs all have an AUC greater than 0.734 (Table 1), with BP26 (BMEI0536; AUC 0.983; Benjamini and Hochberg adjusted Cyber-T p-value<10e-16) giving the best single antigen discrimination with sensitivity and specificity 91% and 96% (Fig. 4), respectively. We used kernel methods and support vector machines [47], [63] to build linear and nonlinear classifiers. As input to the classifier, we used the highest-ranking 1, 2, 5, 10, 13 ORFs on the basis of single antigen AUC. The results show that increasing the antigen number from 2 to 5 produced an improvement in sensitivity and specificity (Fig. 4). This classifier yielded a high sensitivity and specificity rate of 95% and 96%, respectively.

Bottom Line:
To better understand the universe of antibody responses that develop after B. melitensis infection, a protein microarray was fabricated containing 1,406 predicted B. melitensis proteins.Based on these results, a nitrocellulose line blot containing the human serodiagnostic antigens was fabricated and applied in a simple assay that validated the accuracy of the protein microarray results in the diagnosis of humans.These data demonstrate that an experimentally infected natural reservoir host produces a fundamentally different immune response than a naturally infected accidental human host.

ABSTRACTBrucellosis is a widespread zoonotic disease that is also a potential agent of bioterrorism. Current serological assays to diagnose human brucellosis in clinical settings are based on detection of agglutinating anti-LPS antibodies. To better understand the universe of antibody responses that develop after B. melitensis infection, a protein microarray was fabricated containing 1,406 predicted B. melitensis proteins. The array was probed with sera from experimentally infected goats and naturally infected humans from an endemic region in Peru. The assay identified 18 antigens differentially recognized by infected and non-infected goats, and 13 serodiagnostic antigens that differentiate human patients proven to have acute brucellosis from syndromically similar patients. There were 31 cross-reactive antigens in healthy goats and 20 cross-reactive antigens in healthy humans. Only two of the serodiagnostic antigens and eight of the cross-reactive antigens overlap between humans and goats. Based on these results, a nitrocellulose line blot containing the human serodiagnostic antigens was fabricated and applied in a simple assay that validated the accuracy of the protein microarray results in the diagnosis of humans. These data demonstrate that an experimentally infected natural reservoir host produces a fundamentally different immune response than a naturally infected accidental human host.